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Performances of automated digital imaging of Gram-stained slides with on-screen reading against manual microscopy

Authors :
Gesuele Renzi
Adrien Nicolas Fischer
Nicolas Vuilleumier
Nouria Azam
Lara Rasga
Jacques Schrenzel
Valérie Barras
Abdessalam Cherkaoui
Manuela Tangomo
Source :
European Journal of Clinical Microbiology & Infectious Diseases, European Journal of Clinical Microbiology & Infectious Diseases, Vol. 40, No 10 (2021) pp. 2171-2176
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

The objective of this study was to evaluate the performances of the automated digital imaging of Gram-stained slides against manual microscopy. Four hundred forty-three identified Gram-stained slides were included in this study. When both methods agreed, we considered the results as correct, and no further examination was carried out. Whenever the methods gave discrepant results, we reviewed the digital images and the glass slides by manual microscopy to avoid incorrectly read smears. The final result was a consensus of multiple independent reader interpretations. Among the 443 slides analyzed in this study, 101 (22.8%) showed discrepant results between the compared methods. The rates of discrepant results according to the specimen types were 5.7% (9/157) for positive blood cultures, 42% (60/142) for respiratory tract specimens, and 22% (32/144) for sterile site specimens. After a subsequent review of the discrepant slides, the final rate of discrepancies dropped to 7.0% (31/443). The overall agreement between the compared methods and the culture results reached 78% (345/443) and 79% (349/443) for manual microscopy and automated digital imaging, respectively. According to culture results, the specificity for automated digital imaging and manual microscopy were 90.8% and 87.7% respectively. In contrast, sensitivity was 84.1% for the two compared methods. The discrepant results were mostly encountered with microorganism morphologies of rare occurrence. The results reported in this study emphasize that on-screen reading is challenging, since the recognition of morphologies on-screen can appear different as compared to routine manual microscopy. Monitoring of Gram stain errors, which is facilitated by automated digital imaging, remains crucial for the quality control of reported Gram stain results.

Details

ISSN :
14354373 and 09349723
Volume :
40
Database :
OpenAIRE
Journal :
European Journal of Clinical Microbiology & Infectious Diseases
Accession number :
edsair.doi.dedup.....57b0e8eec2fbfb06d7051b6b98c0a74e
Full Text :
https://doi.org/10.1007/s10096-021-04233-2